Job Description
Are you a visionary scientist ready to bridge the gap between complex biological data and actionable insights? GenoTech Solutions is seeking a highly skilled Senior Data Scientist to join our elite R&D team in San Diego.
We are pioneering the future of personalized medicine. In this pivotal role, you will apply cutting-edge machine learning techniques to analyze massive genomic datasets, accelerating drug discovery and patient outcomes. If you thrive in a fast-paced, innovative environment and want to make a tangible impact on global health, we want to hear from you.
Why Join Us?
- Competitive Compensation: Annual salary between $140k and $180k, plus equity.
- Health & Wellness: Comprehensive medical, dental, and vision coverage.
- Work-Life Balance: Flexible hybrid work schedule and generous PTO.
- Growth: Access to top-tier training and conference attendance.
At GenoTech, we value diversity and are committed to an inclusive environment for all employees.
Responsibilities
- Model Development: Design, implement, and optimize complex machine learning models to predict protein structures and disease markers.
- Data Engineering: Build scalable data pipelines to ingest, clean, and process high-throughput sequencing data.
- Collaboration: Partner with cross-functional teams of biologists, clinicians, and software engineers to translate biological questions into technical solutions.
- Research & Innovation: Stay abreast of the latest advancements in bioinformatics and apply novel algorithms to our research projects.
- Communication: Present technical findings and model performance metrics to senior leadership and external stakeholders clearly and concisely.
Qualifications
- Education: PhD or Master’s degree in Bioinformatics, Computational Biology, Statistics, Computer Science, or a related scientific field.
- Experience: Minimum of 5 years of professional experience in data science, with a focus on biological data.
- Technical Skills: Proficiency in Python (PyTorch/TensorFlow), R, SQL, and Hadoop/Spark ecosystems.
- Domain Knowledge: Strong understanding of genomics, molecular biology, or related scientific domains.
- Problem Solving: Demonstrated ability to solve complex, unstructured problems using statistical and computational methods.